What is machine learning and how does Netflix use it for its recommendation engine?

What is machine learning and how does Netflix use it for its recommendation engine?

What is machine learning and how does Netflix use it for its recommendation engine?

What is an online recommendation engine?

Think about examples of machine learning you may have encountered in the past such as a website like Netflix  that recommends what video you may be interested in watching next?
Are the recommendations ever wrong or unfair? We will  give an example and explain how this could be addressed.

2023 AWS Certified Machine Learning Specialty (MLS-C01) Practice Exams
2023 AWS Certified Machine Learning Specialty (MLS-C01) Practice Exams

Machine learning is a field of artificial intelligence that Netflix uses to create its recommendation algorithm. The goal of machine learning is to teach computers to learn from data and make predictions based on that data. To do this, Netflix employs Machine Learning Engineers, Data Scientists, and software developers to design and build algorithms that can automatically improve over time. The Netflix recommendations engine is just one example of how machine learning can be used to improve the user experience. By understanding what users watch and why, the recommendations engine can provide tailored suggestions that help users find new shows and movies to enjoy. Machine learning is also used for other Netflix features, such as predicting which shows a user might be interested in watching next, or detecting inappropriate content. In a world where data is becoming increasingly important, machine learning will continue to play a vital role in helping Netflix deliver a great experience to its users.

What is machine learning and how does Netflix use it for its recommendation engine?
What is machine learning and how does Netflix use it for its recommendation engine?

Netflix’s recommendation engine is one of the company’s most valuable assets. By using machine learning, Netflix is able to constantly improve its recommendations for each individual user.

Machine learning engineers, data scientists, and developers work together to build and improve the recommendation engine.

  • They start by collecting data on what users watch and how they interact with the Netflix interface.
  • This data is then used to train machine learning models.
  • The models are constantly being tweaked and improved by the team of engineers.
  • The goal is to make sure that each user sees recommendations that are highly relevant to their interests.

Thanks to the work of the team, Netflix’s recommendation engine is constantly getting better at understanding each individual user.

How Does It Work?

In short, Netflix’s recommendation algorithm looks at what you’ve watched in the past and then makes recommendations based on that data. But of course, it’s a bit more complicated than that. The algorithm also looks at data from other users with similar watching habits to yours. This allows Netflix to give you more tailored recommendations.

For example, say you’re a big fan of Friends (who isn’t?). The algorithm knows that a lot of Friends fans also like shows like Cheers, Seinfeld, and The Office. So, if you’re ever feeling nostalgic and in the mood for a sitcom marathon, Netflix will be there to help you out.

But That’s Not All…

Not only does the algorithm take into account what you’ve watched in the past, but it also looks at what you’re currently watching. For example, let’s say you’re halfway through Season 2 of Breaking Bad and you decide to take a break for a few days. When you come back and finish Season 2, the algorithm knows that you’re now interested in similar shows like Dexter and The Wire. And voila! Those shows will now be recommended to you.

Of course, the algorithm isn’t perfect. There are always going to be times when it recommends a show or movie that just doesn’t interest you. But hey, that’s why they have the “thumbs up/thumbs down” feature. Just give those shows the old thumbs down and never think about them again! Problem solved.

Another angle :

When it comes to TV and movie recommendations, there are two main types of data that are being collected and analyzed:

1) demographic data

2) viewing data.

Demographic data is information like your age, gender, location, etc. This data is generally used to group people with similar interests together so that they can be served more targeted recommendations. For example, if you’re a 25-year-old female living in Los Angeles, you might be grouped together with other 25-year-old females living in Los Angeles who have similar viewing habits as you.

Viewing data is exactly what it sounds like—it’s information on what TV shows and movies you’ve watched in the past. This data is used to identify patterns in your viewing habits so that the algorithm can make better recommendations on what you might want to watch next. For example, if you’ve watched a lot of romantic comedies in the past, the algorithm might recommend other romantic comedies that you might like based on those patterns.

Are the Recommendations Ever Wrong or Unfair?
Yes and no. The fact of the matter is that no algorithm is perfect—there will always be some error involved. However, these errors are usually minor and don’t have a major impact on our lives. In fact, we often don’t even notice them!

The bigger issue with machine learning isn’t inaccuracy; it’s bias. Because algorithms are designed by humans, they often contain human biases that can seep into the recommendations they make. For example, a recent study found that Amazon’s algorithms were biased against women authors because the majority of book purchases on the site were made by men. As a result, Amazon’s algorithms were more likely to recommend books written by men over books written by women—regardless of quality or popularity.

These sorts of biases can have major impacts on our lives because they can dictate what we see and don’t see online. If we’re only seeing content that reflects our own biases back at us, we’re not getting a well-rounded view of the world—and that can have serious implications for both our personal lives and society as a whole.

One of the benefits of machine learning is that it can help us make better decisions. For example, if you’re trying to decide what movie to watch on Netflix, the site will use your past viewing history to recommend movies that you might like. This is possible because machine learning algorithms are able to identify patterns in data.

Another benefit of machine learning is that it can help us automate tasks. For example, if you’re a cashier and have to scan the barcodes of the items someone is buying, a machine learning algorithm can be used to automatically scan the barcodes and calculate the total cost of the purchase. This can save time and increase efficiency.

The Consequences of Machine Learning

While machine learning can be beneficial, there are also some potential consequences that should be considered. One consequence is that machine learning algorithms can perpetuate bias. For example, if you’re using a machine learning algorithm to recommend movies to people on Netflix, the algorithm might only recommend movies that are similar to ones that people have already watched. This could lead to people only watching movies that confirm their existing beliefs instead of challenged them.

Another consequence of machine learning is that it can be difficult to understand how the algorithms work. This is because the algorithms are usually created by trained experts and then fine-tuned through trial and error. As a result, regular people often don’t know how or why certain decisions are being made by machines. This lack of transparency can lead to mistrust and frustration.

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    by /u/Jooniesnamu (Netflix) on July 12, 2024 at 6:53 am

    Hi everyone! I’m doing research regarding a product redesign of Netflix for my UX design class. If you have some time could you please take this survey? Thanks so much! https://docs.google.com/forms/d/e/1FAIpQLScg0dEVtGPLPrKKkWnxi7rsPJ-MslUg0C8bCekfICcmWOrv6g/viewform?usp=send_form submitted by /u/Jooniesnamu [link] [comments]

  • Kota factory viewer here
    by /u/Aware-Spirit4880 (Netflix) on July 12, 2024 at 6:49 am

    Hello everyone, I hope you're all doing well. I recently watched the Indian series "Kota Factory" and it quickly became one of my favorites. I think the reason for this is that I can relate to the characters and the intense study pressure they face, as I'm going through a similar situation right now. My favorite scene was at the end of season 3, where Vaibhav, the main character, fails the exam while all his friends pass, and their beloved teacher "Jeetu Bhaiya" leaves the city. It was so heartbreaking that it brought me to tears. Sorry if this sounds like a spoiler, but I had to share. Has anyone else watched it? What do you think—will there be a season 4, or was this the final season? submitted by /u/Aware-Spirit4880 [link] [comments]

  • Which Iconic Character or Music Legend Are You?
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  • How do I get Netflix to consider licensing this Epic-as-Hell French Cartoon Film 'Dofus'?
    by /u/saint_rocky (Netflix) on July 12, 2024 at 6:46 am

    I'm pitching this idea (or rather getting direction on how to pitch it) because as an animimation-phile I am in AGONY ever since finally watching through this obscure flash+traditional animated French film called "Dofus" from about nine years ago. I could not believe how amazing it was as probably the best marriage between western and anime animation styles and techniques, and even with the ocassional obviousness of the mega-high-frame-Flash coming out, most of the time you thought you were watching a best-era Disney 2D film simply helmed by a bunch of brilliant anime nerds. Here is a link to one of the best fight sequences in the film and you'll see what I mean. HUGE SPOILER ALERT: https://www.youtube.com/watch?v=0YYaeR3cM-A So: This movie was a bit of a failure. It had a weird title, was based on an obscure MMORPG game series with an even weirder title, and from what I can tell only released in France theatrically. From there it was never licensed in other countries and, most sadly, never dubbed into English where it would most certaintly have doubled its following and then some. Most of us media fiends are aware that it's a regular but unfortunate thing when an objectively good project gets no noteriety upon release due to bad marketing and other decisions that lead to limited reception upon release. So my pitch is that Netflix go for the jugular on this one. 'Dofus' is about to get its 10th anniversery and I think it's the perfect "excuse" for Netflix to pick it up and spend a generous amount on a well-casted, well internationalized english voice version of this first installment of Dofus saga. I believe that through Netflix picking it up, advertising it with a *GOOD* (and not awkward literally translated) english dub, it will get the popularity it is entitled to and this will give it the fuel and capital necessary for the main creators of the film to return to Dofus and begin working on its 2nd 'book', which they are on record saying they want to do. Does anybody here know a smart way we can get this birdie in a Netflix rep's ear? Or is it somehow gonna be smarter to just start a go-fund-me for a quality English dub and redistributing of Dofus by any decent distributor in hopes of giving it momentum again? Because the main reason I wanna start with Netflix with this idea is because I respect their consistent belief in 2d animation, even during its ebbs and flows. Thanks for all insights in advance. submitted by /u/saint_rocky [link] [comments]

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    by /u/Certain_Passion1630 (Netflix) on July 12, 2024 at 5:55 am

    I would guess this has been brought up before, but I just recently watched the movie. If the parents get married, the kids are now married step siblings. Obviously, there is no blood relation, so it’s not wrong. But I feel like it would make some weird dynamics, like Emma’s stepdad being her father-in-law. submitted by /u/Certain_Passion1630 [link] [comments]

  • "Love Again" (2023) - Enjoyable through the lens of a Netflix watch
    by /u/KakoiKagakusha (Netflix) on July 12, 2024 at 3:06 am

    Just watched this romance movie (more drama maybe than comedy), which apparently came out in theaters last summer and apparently did terribly. It's got the dude from Outlander (SASSENACH!), Priyanka Chopra Jonas, and an unexpected amount of Céline Dion. My wife and I really enjoyed it for what it was, which is a relatively light and enjoyable romantic movie. Some issues one can pick on for sure (see the threads from last summer with ppl who paid to see it in theaters), but watching this in bed on Netflix, an easy recommend if you're looking for this kind of movie. submitted by /u/KakoiKagakusha [link] [comments]

  • Netflix extra member feature not working correctly.
    by /u/Lion-heart_1040 (Netflix) on July 12, 2024 at 2:08 am

    So i have the standard (2-screen) plan and i purchased the extra member add-on because my sister doesnt live here. So technically we are supposed to have 3 screens at a time (2 in this house, 1 outside the house.) note: i have a screenshot of netflix employee on chat confirming this when i first added the extra member. turning on netflix today and clicking on a movie to watch, it told me i already have two screens watching: my brother (who is in the basement rn) and my sister (who is watching at her house). WTF? This is too complicated now. submitted by /u/Lion-heart_1040 [link] [comments]

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    ��👉👉 WATCH & DOWNLOAD ��👉👉 https://1movie.xyz/movie/762441/a-quiet-place-nbsp-day-one.htmlContinue reading on Medium »

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    by /u/Vleaides (Netflix) on July 12, 2024 at 12:18 am

    Basically tittle. evil only recently came to netflix but it has 100% on rotten tomatoes and also is the 7th most watched TV show atm. the show is actually so damn good I really hope netflix picks it up as it seems like it was only cancelled due to writers strike. idk, what do you guys think? submitted by /u/Vleaides [link] [comments]

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    by /u/browhyiseveryuser (Netflix) on July 11, 2024 at 11:45 pm

    so everytime i’m on netflix and i go on my computer to watch the walking dead it brings me back to season seven episode eleven, aka rock in the road, yet im on season ten, episode eleven of the show and i really don’t know how to fix it, but i want to cause it’s really annoying to have to skip to the end of the season, go to the next episode and keep on doing that just to watch it, can somebody help me fix this? i’ve tried a lot of stuff yet that hasn’t helped it, i would appreciate it if i did get help from someone. submitted by /u/browhyiseveryuser [link] [comments]

  • The River Wild 2023
    by /u/tonymontana905 (Netflix) on July 11, 2024 at 11:45 pm

    Omg this move actually was soo terrible I almost fell asleep during it. Terrible acting, terrible plot. Everything and everyone was so predictable! Two hours I won’t be able to recover ever. Ugh then there’s the fight in the river the big guy is literally twcie the size of the little guy! Then there’s the struggle for the gun and of course the gunshot and we all know who came out of that one alive omg! This movie is sooooo bad ! submitted by /u/tonymontana905 [link] [comments]

  • Netflix is ​​getting boring
    by /u/Unusual-Word-7598 (Netflix) on July 11, 2024 at 11:17 pm

    Because I watch high-level series/movies with strong productions, I can no longer watch some regular movies and series because they no longer interest me. Please, I need the best and strongest films and series, wonderful and interesting, and preferably, from my point of view, not famous. Your suggestion? submitted by /u/Unusual-Word-7598 [link] [comments]

  • Any recommendation?
    by /u/BioResearch7 (Netflix) on July 11, 2024 at 10:47 pm

    So this list is few years old but you kinda get the gist, i have watched plenty since then… off from uni so give your suggestions! [x] Scandal [x] Firefly [x] Outlander [x] Dexter [x] Arrow [x] Narcos [x] Frontier [x] Billions [x] Izombie [x] Colombiana [x] The defenders [x] Daredevil [x] The expanse [x] Shadow and bone [x] Dota: dragon’s blood [x] Power [x] Poldark [x] Tribes of Europa [x] Lupin [x] Fate [x] Marvel’s agents of shield [x] See [x] Ozark [x] Bridgerton [x] Cobra kai [x] The blacklist [x] Designed survivor [x] How i met your mother [x] Carnival row [x] Queen of South [x] The foreigner [x] White gold [x] The mandalorian [x] Dynasty [x] Timeless [x] Sense8 [x] Never have I ever [x] Shannara [x] Outer banks [x] Trinkets [x] How to get away with murder [x] the shannara chronicles 1-2 [x] Merlin [x] Travelers [x] The expanding universe of Ashley G [x] Reign [x] Omniscient [x] Marco polo [x] Troy fall of the city [x] 13 reasons why [x] Scorpion [x] Salvation [x] Shooter [x] The end of fung world [x] White collar [x] Bitten [x] Atypical [x] Insatiable [x] Anne with an e [x] Sex education [x] Van helsing [x] Rise of Ottoman Empire [x] V warz [x] You [x] Homeland [x] Rome [x] The last kingdom [x] Spartacus [x] Friends [x] The big bang theory [x] Orange is new black [x] Teen wolf [x] Riverdale [x] House of cards [x] The witcher [x] Jack ryan [x] Expanse [x] Star Trek (Discovery) [x] The Vampire dairies [x] The originals [x] Legacies [x] Lost in space [x] The 100 [x] Prison break [x] Altered carbon [x] Iron fist [x] Shameless [x] Bansheee [x] Bodyguard [x] Another life submitted by /u/BioResearch7 [link] [comments]

  • Has there ever been a movie so generic you accidentally watched it twice?
    by /u/Thunder_Punt (Movie News and Discussion) on July 11, 2024 at 10:43 pm

    For me it was a movie called 'The Silence' with Stanley Tucci. I genuinely watched that movie and only when I recognised some set designs and started predicting stuff in one of the final scenes did I go 'oh, I've seen this before.'. Something about the concept being a quite generic birdbox/a quiet place gimmick and the movie just being overall forgettable meant that I watched most of it without recognising that I'd seen it before. I couldn't tell you much about it now, even though I've seen it twice. submitted by /u/Thunder_Punt [link] [comments]

  • Help me identify song featured in Sprint (2024)
    by /u/Theres_nothingtosee (Netflix) on July 11, 2024 at 9:49 pm

    Please, I know that somebody can help. There is a song playing in episode 2 27th minute. I tried turning on shazam but nothing came up. The subtitles say, that it’s a song by a brand named TBA. However I searched through almost every damn song by them and none of them match. Is it possible, that the song is just not released yet ? Please somebody help me find the artist and the song. submitted by /u/Theres_nothingtosee [link] [comments]

  • Anyone know any device for offline viewing that can be connect to the TV? (Win app offline mod going to be cancelled)
    by /u/Detvan_SK (Netflix) on July 11, 2024 at 8:13 pm

    Hello, as Netflix is going to turn off offline watching for Windows app with ADs tier update. I wanted to ask what devices have ability to download offline content that ideally can to be connected to some older TV with cable (HDMI, display port etc...). (my phone have only USB-C 2.0 which do not supporting that and app mirroring do not support DRM, also please do not recomend any TV box without Google licencion because lot of time they contain malware) Lot of time I have problems with connectivity due some rooms, old router (that I would like to switch for newer just family do not want to), sometime even turning off it due a thunderstorm, or simply on traveling. Did someone have any experiences with non-Windows devices that can download content from Netflix and ideally playing it on the TV from that? And ideally are not too much expensive. submitted by /u/Detvan_SK [link] [comments]

  • Netflix freezing on a frame, but the audio keeps playing (mobile)
    by /u/Nexed_ (Netflix) on July 11, 2024 at 8:05 pm

    It only happens on my phone. I've tried restarting my phone, restarting wifi, using phone data, clearing data and cache, and nothing works. It happens pretty often and it's annoying. The only fix I found was quit from a movie or an episode, go back into it again and skip that part. If I try skipping that frozen part without quitting, it will just keep loading forever. submitted by /u/Nexed_ [link] [comments]

  • Some questions about Chestnut Man
    by /u/Giandefeo (Netflix) on July 11, 2024 at 7:50 pm

    Me and my girlfriend just finished Chestnut Man. So here I am with some crucial questions about the plot. I'm gettin crazy: maybe i'm stupid, maybe I missed something. Please help us! ** Spoilers ahead ** Genz and Bekker knew each other? Bekker was covering Genz? Same question about Rasouli-Skans: did they know Genz? How is it possible that the hands and feet were found in their fridge?? Considering the previous questions: was there a more complex plot involving all these people? More about Rasouli-Skans. The threats to Rosa were from Rasouli-Skans? The car that followed the couple was Genz car? Were they murdered by him? Gustav didn't see anything? submitted by /u/Giandefeo [link] [comments]

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